BACKGROUND: In this study we sought to quantify hazards associated with various donor factors into a cumulative risk scoring system (the Pediatric Heart Donor Assessment Tool, or PH-DAT) to predict 1-year mortality after pediatric heart transplantation (PHT). METHODS: PHT data with complete donor information (5,732) were randomly divided into a derivation cohort and a validation cohort (3:1). From the derivation cohort, donor-specific variables associated with 1-year mortality (exploratory p-value < 0.2) were incorporated into a multivariate logistic regression model. Scores were assigned to independent predictors (p < 0.05) based on relative odds ratios (ORs). RESULTS: The final model had an acceptable predictive value (c-statistic = 0.62). The significant 5 variables (ischemic time, stroke as the cause of death, donor-to-recipient height ratio, donor left ventricular ejection fraction, glomerular filtration rate) were used for the scoring system. The validation cohort demonstrated a strong correlation between the observed and expected rates of 1-year mortality (r = 0.87). The risk of 1-year mortality increases by 11% (OR 1.11 [1.08 to 1.14]; p < 0.001) in the derivation cohort and 9% (OR 1.09 [1.04 to 1.14]; p = 0.001) in the validation cohort with an increase of 1-point in score. Mortality risk increased 5 times from the lowest to the highest donor score in this cohort. Based on this model, a donor score range of 10 to 28 predicted 1-year recipient mortality of 11% to 31%. CONCLUSION: This novel pediatric-specific, donor risk scoring system appears capable of predicting post-transplant mortality. Although the PH-DAT may benefit organ allocation and assessment of recipient risk while controlling for donor risk, prospective validation of this model is warranted.
BACKGROUND: In this study we sought to quantify hazards associated with various donor factors into a cumulative risk scoring system (the Pediatric Heart Donor Assessment Tool, or PH-DAT) to predict 1-year mortality after pediatric heart transplantation (PHT). METHODS: PHT data with complete donor information (5,732) were randomly divided into a derivation cohort and a validation cohort (3:1). From the derivation cohort, donor-specific variables associated with 1-year mortality (exploratory p-value < 0.2) were incorporated into a multivariate logistic regression model. Scores were assigned to independent predictors (p < 0.05) based on relative odds ratios (ORs). RESULTS: The final model had an acceptable predictive value (c-statistic = 0.62). The significant 5 variables (ischemic time, stroke as the cause of death, donor-to-recipient height ratio, donor left ventricular ejection fraction, glomerular filtration rate) were used for the scoring system. The validation cohort demonstrated a strong correlation between the observed and expected rates of 1-year mortality (r = 0.87). The risk of 1-year mortality increases by 11% (OR 1.11 [1.08 to 1.14]; p < 0.001) in the derivation cohort and 9% (OR 1.09 [1.04 to 1.14]; p = 0.001) in the validation cohort with an increase of 1-point in score. Mortality risk increased 5 times from the lowest to the highest donor score in this cohort. Based on this model, a donor score range of 10 to 28 predicted 1-year recipient mortality of 11% to 31%. CONCLUSION: This novel pediatric-specific, donor risk scoring system appears capable of predicting post-transplant mortality. Although the PH-DAT may benefit organ allocation and assessment of recipient risk while controlling for donor risk, prospective validation of this model is warranted.
Authors: Ryan J Williams; Minmin Lu; Lynn A Sleeper; Elizabeth D Blume; Paul Esteso; Francis Fynn-Thompson; Christina J Vanderpluym; Simone Urbach; Kevin P Daly Journal: Am J Transplant Date: 2022-02-08 Impact factor: 9.369
Authors: Alia Dani; Justin S Heidel; Tingting Qiu; Yin Zhang; Yizhao Ni; Md Monir Hossain; Clifford Chin; David L S Morales; Bin Huang; Farhan Zafar Journal: Pediatr Transplant Date: 2021-12-08
Authors: Farhan Zafar; Md Monir Hossain; Yin Zhang; Alia Dani; Marc Schecter; Don Hayes; Maurizio Macaluso; Christopher Towe; David L S Morales Journal: Transplantation Date: 2022-04-06 Impact factor: 5.385